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Record W2084081959 · doi:10.4161/cc.6.3.3795

To Die or Not to Die: Neurons and p63

2007· review· de· W2084081959 on OpenAlexaff
Freda D. Miller, David R. Kaplan

Bibliographic record

VenueCell Cycle · 2007
Typereview
Languagede
FieldMedicine
TopicCancer-related Molecular Pathways
Canadian institutionsSickKids FoundationHospital for Sick Children
Fundersnot available
KeywordsBiologyNeuroscienceNervous system

Abstract

fetched live from OpenAlex

One of the fundamental questions in neurobiology is how mammalian neurons survive for an organism's lifetime in the face of normal ongoing "wear and tear" that, in the case of neurons in the peripheral nervous system, even includes physical damage. Elucidating the mechanisms that control neuronal survival is of importance not only for our understanding of normal development of neuronal circuitry, but also to devise treatments for pathological situations such as traumatic injury, or neurodegenerative conditions. In this review, we will cover the emerging evidence that p63 plays an essential role in regulating neuronal life and death decisions in the nervous system working in concert with its two other family members, p53 and p73.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.002

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.046
GPT teacher head0.334
Teacher spread0.288 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations19
Published2007
Admission routes1
Has abstractyes

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